theanorc_gpu

[global]
floatX = float32
device = gpu
openmp = True
openmp_elem_wise = 200000

[dnn]
enabled = True
include_path = /reg/neh/home/davidsch/cudnn_v4/lib/cuda/include
library_path =  /reg/neh/home/davidsch/cudnn_v4/lib/cuda/lib64

[dnn.conv]
algo_fwd = small
#(('small', 'none', 'large', 'fft', 'fft_tiling', 'guess_once', 'guess_on_shape_change', 'time_once', 'time_on_shape_change')) 
#    Doc:  Default implementation to use for CuDNN forward convolution.
#    Value:  small

algo_bwd_data = none
#(('none', 'deterministic', 'fft', 'fft_tiling', 'guess_once', 'guess_on_shape_change', 'time_once', 'time_on_shape_change')) 
#    Doc:  Default implementation to use for CuDNN backward convolution to get the gradients of the convolution with regard to the inputs.
#    Value:  none

algo_bwd_filter = none
#(('none', 'deterministic', 'fft', 'small', 'guess_once', 'guess_on_shape_change', 'time_once', 'time_on_shape_change')) 
#    Doc:  Default implementation to use for CuDNN backward convolution to get the gradients of the convolution with regard to the filters.
#    Value:  none

precision = as_input
#(('as_input', 'float16', 'float32', 'float64')) 
#    Doc:  Default data precision to use for the computation in CuDNN convolutions (defaults to the same dtype as the inputs of the convolutions).
#    Value:  as_input

[nvcc]
fastmath = False